DOI: 10.3724/SP.J.1249.2018.02158

Journal of Shenzhen University Science and Engineering (深圳大学学报理工版) 2018/35:2 PP.158-165

Pedometer method based on adaptive multilevel thresholding

The step counter plays an important role in the smart phone and intelligent wearable device. It has been widely used in the fields of body building, medical treatment, and navigation. In order to handle the performance degradation caused by various motion states and non-walking interference, e.g., waist's shaking, in existing pedometer methods, we propose a novel pedometer method based on the adaptive multilevel thresholding technology, which can be divided into three thresholds controlling. Firstly, it finds the peaks and valleys by using the accelerometer data. Secondly, it calculates the frequency characteristic of human's movement based on the obtained peaks and valleys, and subsequently determines the motion state (such as walking slowly, walking fast or running). Thirdly, it adaptively assigns the time threshold and peak-valley threshold according to the estimated motion states to achieve step counting. Experimental results show that the proposed algorithm can adapt to different motion states and different sensor mounting positions, and obtain an average accuracy rate above 95%.

Key words:information processing technology,step counter,adaptive,multilevel thresholding,walking frequency characteristic,three-axis accelerometer,wearable device

ReleaseDate:2018-03-20 15:26:57

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